THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°36)

Patch 2.21 - Week 1 - Ionia don’t be broken challenge: Impossible

Valentino (Legna) Vazzoler
12-15-2021

Data

Note: With the current Season I want to start using a “more robust” way for which games to collect. Reason being that while I want to focus on Master players it’s possible to notice the flaw that

So the proposed solution is the following:


Number of (Ranked) matches analysed 62413 or 124826 games. / LastSeasonal Players

Number of (Ranked) matches analysed 6834 or 13668 games. / ~HighDiamond

Last Update: 2021-12-12 16:14

Patch 2.21 - Week 1 - by the Numbers1
Characteristic3 Last Seasonal2 ~HighDiamond2
N = 89,5574 N = 62,4134 N = 7,6494 N = 6,8344
Status
Ranked 62,413 (70%) 6,834 (89%)
Other 24,322 (27%) 673 (8.8%)
Friendly 2,822 (3.2%) 142 (1.9%)
Server
americas 43,920 (49%) 29,626 (47%) 4,038 (53%) 3,505 (51%)
asia 9,683 (11%) 7,220 (12%) 1,136 (15%) 1,069 (16%)
europe 35,954 (40%) 25,567 (41%) 2,475 (32%) 2,260 (33%)

1 Max datetime recovered: 2021-12-12 13:56:14 UTC from 2021-12-08 18:00:00 to 2021-12-15 18:00:00 UTC

2 EU Master playerDecks in the ladder 10 while number of possible Master playerDecks recovered is 10 NA Master playerDecks in the ladder 14 while number of possible Master playerDecks recovered is 14 ASIA Master playerDecks in the ladder 5 while number of possible Master playerDecks recovered is 5

3 Metadata from Friendly Matches (that aren't Bo3) is not recoverable, the value may not be perfect since I lack the starting time of the game. The amount of Games to still scrap is also an estimation based on the 'position' of the game

4 n(%) took from the number of matches. When the data is analysed the size is double since we account each different player

Regions

Play Rate

Plot

The Gini Index is a measure of heterogeneity so, in this case and in simpler terms, how much the play rates are similar. The Index goes (when normalized like here) \(in\) [0,1] and it’s equal to 1 when there’s a single value with 100% play rate or 0 when all play rates are equal. Of course a Gini Index of 1 needs to be avoided but it’s not like the aim should be 0. As said, it’s just to add some additional tools.

Table

Region Play Rate
Relative Frequencies by Inclusion Rate of a Region
Region Freq Shard
America Asia Europe
BandleCity 19.79% 19.73% 21.52% 19.39%
Ionia 15.65% 15.63% 16.05% 15.57%
Demacia 12.95% 13.06% 11.07% 13.35%
Piltover 11.68% 11.46% 12.57% 11.68%
Noxus 9.80% 9.65% 9.80% 9.98%
MtTargon 9.10% 9.07% 7.48% 9.58%
Bilgewater 6.87% 7.16% 6.32% 6.69%
Freljord 5.18% 4.95% 4.76% 5.56%
Shurima 4.62% 4.92% 6.00% 3.88%
ShadowIsles 4.36% 4.39% 4.43% 4.31%
Patch 2.21 - Week 1 Ranked games from 2021-12-08 18:00:00 UTC to 2021-12-15 18:00:00 UTC Metadata of games collected with RiotGames API

Play Rate by number of Cards

Plot

Table

Region Play Rate
Relative Frequencies by number of times a Card within a Region is included in a Deck
Region Freq Shard
America Asia Europe
Ionia 23.97% 23.99% 25.11% 23.63%
BandleCity 23.22% 23.00% 25.55% 22.82%
Demacia 10.26% 10.52% 8.22% 10.53%
MtTargon 9.70% 9.71% 7.76% 10.25%
Bilgewater 8.55% 8.68% 7.11% 8.79%
Noxus 7.45% 7.22% 7.32% 7.76%
Piltover 5.58% 5.54% 5.94% 5.52%
Shurima 4.05% 4.27% 5.26% 3.46%
ShadowIsles 3.74% 3.75% 3.95% 3.68%
Freljord 3.47% 3.32% 3.78% 3.56%
Patch 2.21 - Week 1 Ranked games from 2021-12-08 18:00:00 UTC to 2021-12-15 18:00:00 UTC Metadata of games collected with RiotGames API

Champions Combinations

Play Rates

Plot

from Last-Seasononal

Data from Last-Season Master Only. Source: Source: Metadata of games collected with RiotGames API FALSE

from ~HighDiamond

Data from Current Master Only. Source: Source: Metadata of games collected with RiotGames API FALSE

Day by Day

Highlisting the top10 most played decks (at the moment of the last game played).

Win Rates

Tie games are excluded

Meta Decks

Win rates of the most played combination of champions. Play Rate >= 1% in at least one of the servers.

Underdog

Top Win rates of the top10 best performing least played combination of champions. Play rate \(\in\) [0.1%,1%)1

Match Ups

Note:: only games from Last-Season Master

Regarding MU, this is not the most accurate estimation you can get from my data. If you want a better picture of the current meta it would be better to look at the dedicated MU-page where I use all “Ranked” games with the current sets of buffs and nerfs. While one may object I don’t account for optimizations and differences in skills acquired during the weeks, the overall number of games / sample size makes them a better source of information. So, in case, please refer to the MU - page for a better “meta-investigation”.

Match-up Grid

The win rates on the grid are among the 15 most played champion combination. The upper value is from all the Last-Season Masters, the bottom one only from the current Current Masters. MU with less than 30 games are not included.

Ezreal/Kennen (IO/PZ) Poppy/Teemo (BC/DE) Pantheon/Taric (DE/MT) Gangplank/Sejuani Lulu/Poppy (BC/DE) Gangplank/Twisted Fate (BC/BW) Poppy/Ziggs (BC/NX) Pantheon/Riven Ahri/Fizz (BC/IO) Ahri/Kennen Senna/Veigar Pyke/Rek'Sai Kennen/Poppy (BC/NX) Lissandra/Taliyah Ahri/Kennen (IO/SH)
Ezreal/Kennen (IO/PZ)
NA
41.0%
46.4%
62.4%
68.3%
54.9%
59.2%
54.6%
53.9%
39.3%
45.2%
53.0%
58.2%
66.8%
62.5%
59.0%
63.0%
50.3%
55.6%
65.0%
66.7%
45.5%
52.9%
33.3%
27.3%
53.6%
Poppy/Teemo (BC/DE)
59.0%
53.6%
NA
43.8%
40.0%
53.6%
39.7%
58.4%
54.9%
68.6%
69.0%
51.4%
44.8%
46.3%
71.8%
61.6%
63.1%
61.1%
37.8%
36.8%
59.3%
68.1%
63.6%
67.1%
Pantheon/Taric (DE/MT)
37.6%
31.7%
56.2%
60.0%
NA
44.0%
54.8%
67.2%
39.6%
48.1%
24.4%
47.0%
57.1%
45.9%
43.5%
57.3%
36.0%
Gangplank/Sejuani
45.1%
40.8%
46.4%
60.3%
56.0%
NA
41.9%
43.9%
54.4%
48.8%
53.1%
67.5%
45.4%
63.6%
59.8%
47.1%
58.8%
Lulu/Poppy (BC/DE)
45.4%
46.1%
41.6%
45.1%
45.2%
58.1%
NA
57.4%
51.1%
44.0%
56.7%
68.4%
65.1%
53.1%
65.7%
68.3%
58.5%
Gangplank/Twisted Fate (BC/BW)
60.7%
54.8%
31.4%
31.0%
32.8%
56.1%
42.6%
NA
56.4%
33.0%
82.0%
72.5%
47.0%
55.1%
58.6%
36.7%
78.8%
Poppy/Ziggs (BC/NX)
47.0%
41.8%
48.6%
60.4%
45.6%
48.9%
43.6%
NA
55.1%
62.5%
64.4%
56.9%
54.1%
52.0%
59.5%
66.7%
Pantheon/Riven
33.2%
37.5%
55.2%
53.7%
51.9%
51.2%
56.0%
67.0%
44.9%
NA
24.2%
48.1%
44.1%
61.8%
44.8%
56.8%
38.5%
Ahri/Fizz (BC/IO)
41.0%
28.2%
75.6%
46.9%
43.3%
18.0%
37.5%
75.8%
NA
34.5%
37.5%
65.2%
47.9%
33.3%
25.0%
Ahri/Kennen
37.0%
38.4%
53.0%
32.5%
31.6%
27.5%
35.6%
51.9%
65.5%
NA
32.5%
51.1%
46.2%
35.4%
43.3%
Senna/Veigar
49.7%
44.4%
36.9%
38.9%
42.9%
54.6%
34.9%
53.0%
43.1%
55.9%
62.5%
67.5%
NA
38.1%
21.2%
39.3%
57.5%
Pyke/Rek'Sai
35.0%
33.3%
62.2%
63.2%
54.1%
36.4%
46.9%
44.9%
45.9%
38.2%
34.8%
48.9%
61.9%
NA
52.5%
59.0%
52.2%
Kennen/Poppy (BC/NX)
54.5%
47.1%
40.7%
56.5%
40.2%
34.3%
41.4%
48.0%
55.2%
52.1%
53.8%
78.8%
47.5%
NA
51.7%
40.7%
Lissandra/Taliyah
66.7%
72.7%
31.9%
36.4%
42.7%
52.9%
31.7%
63.3%
40.5%
43.2%
66.7%
64.6%
60.7%
41.0%
48.3%
NA
71.4%
Ahri/Kennen (IO/SH)
46.4%
32.9%
64.0%
41.2%
41.5%
21.2%
33.3%
61.5%
75.0%
56.7%
42.5%
47.8%
59.3%
28.6%
NA
The upper value is from Last-Seasononal Players while the bottom value is from ~HighDiamond. MU with less than 30 games are not included. Order of the Archetypes based on the playrate over the last 7 days from the last-update from the upper value population. Source: Metadata of games collected with RiotGames API

Match-up Table

Deck of the week

Fiora/Zed

No new expansion deck? Too boring, better to promote some base-set shenanigans, it’s an old deck but it checks out.

It’s something I saw from sunday stats and well, maybe with all those Yodles it can makes sense.

Deckcodes

How to read the table:
- Play rate: How often a card is included in this class of decks / the table is order by this column.
- 3/2/1 is the relative and absolute frequency of the number of copies in the decks that plays them
- Frequencies from 50% to 100% are colored from shades of green to white to identify more easily the highest values

LoR-Meta Index (LMI)

The LMI 2 3 is an Index I developed to measure the performance of decks in the metagame. For those who are familiar with basic statistical concept I wrote a document to explain the theory behind it: , it’s very similar to vicioussyndicate (vS) Meta Score from their data reaper report. The score of each deck is not just their “strength”, it takes in consideration both play rates and win rates that’s why I prefer to say it measure the “performance”. The values range from 0 to 100 and the higher the value, the higher is the performance.

Static version

Interactive Version

Win Marathons Leaders

Top3 Players (or more in case of ties) from each server that had the highest amount of consecutive wins with the same archetype. The provided deckcode is the one played in the last win found.

Top3 Biggest Win Streak by Server
Cumulative wins with the same Archetype
Player Result Archetype Deck Code
Americas
BBG 20 Ezreal/Kennen (IO/PZ)
FilipeLC 16 Ezreal/Kennen (IO/PZ)
MagnusOTLS 16 Heimerdinger/Jayce (PZ/SI)
Asia
큰거준비중 12 Pantheon/Zoe (IO/MT)
KANDY 10 Ezreal/Kennen (IO/PZ)
pisukaru 10 Sejuani/Teemo (BC/FR)
Usamarer 10 Ezreal/Kennen (IO/PZ)
Europe
timmiTTimmit 18 Pantheon/Riven
Ghosterdriver 17 Sejuani/Trundle/Tryndamere (FR/IO)
solegrozni 14 Ezreal/Kennen (IO/PZ)
Games from all Master are collected each hour adding up to the last 20 matches. Unlikely but possible to miss games in case of high frequency games. Metadata of games collected with RiotGames API

Cards Presence

Play Rate

It seems that not even Twin Disciple can beat Sharsight

Top 3 Play Rates by Region

Forgotten Cards

Cards that couldn’t find place even in a meme deck.

Not-Standard Archetype Names

Names and rules for the “non standard archetypes” which are not defined by Champion+Regions

Archetype ~Fix
Deck Source
ASZ - Sivir Ionia Akshan/Sivir (IO/SH) or Sivir/Zed or Akshan/Sivir/Zed
RubinBait - <Champ> Burn Deck using <Champ> to bait mulligan
Dragons (DE/MT) (DE/MT) Decks with *at least* Shyvana and ASol
SunDisc Mono Shurima with 1+ Sun Disc
Viktor - Shellfolk Viktor + at least one of Curious Shellfolk/Mirror Mage + at least 2 Trinket Trade
Sentinel Control PnZ/SI deck with a combination of Elise/Jayce/Vi

Credits

Special thanks to bA1ance and Pavelicii for the recent support ^^ 4

I may not express gratitude often but that’s because I think the best way I can do it is to continuing working hard on what I do and strive for improvements. Still, proper credits are necessary and I’ll try do it to them more often.

Legal bla bla

This content was created under Riot Games ‘Legal Jibber Jabber’ policy using assets owned by Riot Games. Riot Games does not endorse or sponsor this project.


  1. Min number of games 50, during the times a meta/ladder just changed.↩︎

  2. LMI - Early Theory↩︎

  3. LMI - Adding a Ban Index↩︎

  4. Support page link. In case donations-only the plan is to have the name in the credits for at least a month from the time of the donation.↩︎